It should initially be noted that the method has applications beyond the banking industry, however, for purposes of explanation the banking industry will be utilized as an example.
The process by which banks reach decisions to extend credit to commercial concerns varies in format but is generally universal in approach. The first step is to "spread" the company's financial statements. This is a standard banking term which involves transferring and summarizing the company's balance sheet, income statement and other financial information to a standardized "spread" form, from which ratios and other analytical information are calculated. The concept of spreading financial statements as a basis for financial analysis probably originated at the same time that banks and other financial institutions began analyzing the financial statements of their customers for credit purposes, underwriting of stock or other needs. While the spread forms varied in form by institution, they essentially provided the same information needed to reach the intended decision. Although computerized banking spread programs began to appear in the 1960's and are used more and more, many of the banks in the United States continue to do this by hand. The advent and growth of the personal computer (PC) has accelerated the use of generic mass-market spread-sheet programs (such as Lotus 1-2-3.RTM.. This growth has in turn, fostered the increase in PC based banking spread programs. The primary benefit to these specialized banking programs is to speed the spreading process by automating all of the various calculations needed to be made.
After completing the spread, the next step in reaching a credit decision is to prepare a written analysis of the key financial highlights and trends extracted from the spread to form the financial basis for a credit decision. This is prepared manually by either an analyst or the loan officer and usually requires several hours of time to review the spread, select the key analytical points to be covered in the analysis, develop questions to ask the management of the company to explain or clarify necessary items, then actually write the report. Subsequently, the report will normally be typed, rereviewed by the writer for additions or corrections and retyped as necessary. These reports vary in format and length depending on the policy of the institution, however, the key credit analysis topics reviewed in making a credit decision are largely universal.
Some of the potential shortfalls of this manual process include the overlooking of important analytical points especially by a less experienced individual and errors in figures by the analyst or the typist which are not caught by the individual reviewing the analysis who makes the final decision to make the loan. Since a majority of loans made by commercial banks are not secured by collateral and are primarily based on the analysis of financial statement trends, it is important that all key financial topics be covered accurately in the analysis.
Accordingly, for banking purposes, it would be desirable to have a computerized system which not only provides a format to spread financial statements, but would provide an automated credit analysis report which consistently examines the key analytical topics and makes comments on the financial health and performance of a company. It would further be desirable to have questions recommended to help the individual to fully understand the company's financial situation. The analytical comments and questions would be geared to the financial situation of the particular company and would arise from the examination of a standardized financial database, the spread.
For the purposes of other financial (or statistical) applications, it would be desirable to have a computerized system which could create a complex narrative analytical report from a given financial (or statistical) database The contents of the report if financial, would be geared to the particular financial health and performance of the subject of the database If statistical, the report would analyze the desired attributes of the particular statistical database.